Comparaison des Motifs Svb communs aux S2 et embryon avec les marques d’histones
Alexandra Mancheño Ferris
2/10/2021
- 1 Détermination des motifs fixés par Shavenbaby dans les S2 et les embryons
- 2 Comparaison avec les histones
- 3 Conclusion
1 Détermination des motifs fixés par Shavenbaby dans les S2 et les embryons
1.1 Stringent
## $p.value
## Svb_S2 Svb_embryo. svbF7 pval
## [1,] 0 1 1 NaN
## [2,] 1 0 1 NaN
## [3,] 1 1 0 NaN
##
## $vennCounts
## Svb_S2 Svb_embryo. svbF7 Counts count.B1.peaks count.SvbACT.peaks_embryo
## [1,] 0 0 0 -13114 0 0
## [2,] 0 0 1 1108 0 0
## [3,] 0 1 0 6374 0 6374
## [4,] 0 1 1 581 0 823
## [5,] 1 0 0 3645 3645 0
## [6,] 1 0 1 219 300 0
## [7,] 1 1 0 964 1004 1003
## [8,] 1 1 1 323 563 506
## count.svbF7_cons_gr
## [1,] 0
## [2,] 1108
## [3,] 0
## [4,] 630
## [5,] 0
## [6,] 239
## [7,] 0
## [8,] 377
## attr(,"class")
## [1] "VennCounts"svbF7_motifs_unbound_svb = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$svbF7_cons_gr)
svbF7_motifs_bound_svb = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$`B1.peaks///SvbACT.peaks_embryo///svbF7_cons_gr`)
svbF7_motifs_S2 = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$`B1.peaks///svbF7_cons_gr`)
svbF7_motifs_embryo = as.data.frame(motif_svb_Bind_overlap_cell$peaklist$`SvbACT.peaks_embryo///svbF7_cons_gr`)2 Comparaison avec les histones
2.1 Comparaison sur les motifs fixés dans les S2 et les embryons
2.1.1 H3K27ac
| in H3K27ac | absent H3K27ac | |
|---|---|---|
| in svbF7 unbound | 193 | 745 |
| absent svbF7 unbound | 4955 | 7979 |
| in H3K27ac | absent H3K27ac | |
|---|---|---|
| in svbF7 bound | 267 | 28 |
| absent svbF7 bound | 4886 | 8254 |
presence = c(267,4886)
absence = c(28,8254)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
pvalue_fixe = phyper(193 - 1, 938, 13872 - 938, 5148)
pvalue_nonfixe = phyper(267 - 1, 295, 13435 - 295, 5153)
contingence_H3K27ac_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27ac_fixe)
presence = c(193,4955)
absence = c(745,7979)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27ac_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27ac_nonfixe)La pvalue du test de fisher pour les motifs fixé est de 2.938327510^{-80} Celle du test de fisher pour les motifs non fixé est de 1.590738210^{-29}`
La pvalue du test de hypergéométrique pour les motifs fixé est de 3.611226810^{-30} Celle du test de hypergéométrique pour les motifs non fixé est de 1
total_svbF7_unbound_H3K27ac = 193 + 745
total_svbF7_bound_H3K27ac = 267 + 28
percent_svbf7_H3K27ac_unbound = round(100 * 193 / total_svbF7_unbound_H3K27ac, 2 )
percent_svbf7_unbound_without_H3K27ac = round(100 * 745 / total_svbF7_unbound_H3K27ac, 2 )
percent_svbf7_H3K27ac_bound = round(100 * 267 / total_svbF7_bound_H3K27ac, 2 )
percent_svbf7_bound_without_H3K27ac = round(100 * 28 / total_svbF7_bound_H3K27ac, 2 )
etat_svb = c("svbF7_bound","svb_unbound")
H3K27ac_absent = c(percent_svbf7_bound_without_H3K27ac,percent_svbf7_unbound_without_H3K27ac)
H3K27ac_present = c(percent_svbf7_H3K27ac_bound,percent_svbf7_H3K27ac_unbound)
data_H3K27ac = data.frame(etat_svb,H3K27ac_absent,H3K27ac_present)
datatable(data_H3K27ac,rownames = F,filter = "none",colnames = c("Regions without H3K27ac","Regions with H3K27ac" ))fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb")
fig1fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig12.1.2 H3K27me3
| in H3K27me3 | absent H3K27me3 | |
|---|---|---|
| in svbF7 unbound | 1241 | 0 |
| absent svbF7 unbound | 12191 | 4566 |
| in H3K27me3 | absent H3K27ac | |
|---|---|---|
| in svbF7 bound | 190 | 105 |
| absent svbF7 bound | 13248 | 3723 |
pvalue_fixe = phyper(190 - 1, 295, 17266 - 295, 13438)
pvalue_nonfixe = phyper(1241 - 1, 938, 17998 - 938, 13432)
presence = c(190,13248)
absence = c(105,3723)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27me3_fixe)
presence = c(1241,12191)
absence = c(0,4566)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27me3_nonfixe)La pvalue du test de fisher pour les motifs fixé est de 1.255137810^{-7} Celle du test de fisher pour les motifs non fixé est de 8.667719310^{-165}`
La pvalue du test de hypergéométrique pour les motifs fixé est de 3.998180410^{-8} Celle du test de hypergéométrique pour les motifs non fixé est de 1
total_svbF7_unbound_H3K27me3 = 1241 + 0
total_svbF7_bound_H3K27me3 = 190 + 105
percent_svbf7_H3K27me3_unbound = round(100 * 1241 / total_svbF7_unbound_H3K27me3, 2 )
percent_svbf7_unbound_without_H3K27me3 = round(100 * 0 / total_svbF7_unbound_H3K27me3, 2 )
percent_svbf7_H3K27me3_bound = round(100 * 190 / total_svbF7_bound_H3K27me3, 2 )
percent_svbf7_bound_without_H3K27me3 = round(100 * 105 / total_svbF7_bound_H3K27me3, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K27me3_absent = c(percent_svbf7_bound_without_H3K27me3,percent_svbf7_unbound_without_H3K27me3)
H3K27me3_present = c(percent_svbf7_H3K27me3_bound,percent_svbf7_H3K27me3_unbound)
data_H3K27me3 = data.frame(etat_svb,H3K27me3_absent,H3K27me3_present)
datatable(data_H3K27me3,rownames = F,filter = "none",colnames = c("Regions without H3K27me3","Regions with H3K27me3" ))fig2 = plot_ly(data_H3K27me3, x = ~etat_svb,y = ~H3K27me3_absent, type = "bar",name = "H3K27me3 absent")
fig2 = fig2 %>% add_trace(y = ~H3K27me3_present, name = "H3K27me3 present")
fig2 = fig2 %>% layout(yaxis = list(title = "percent"))
fig2 = fig2 %>% layout(title = "H3K27me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig22.1.3 H3K4me1
| in H3K4me1 | absent H3K4me1 | |
|---|---|---|
| in svbF7 unbound | 324 | 614 |
| absent svbF7 unbound | 8441 | 6309 |
| in H3K4me1 | absent H3K4me1 | |
|---|---|---|
| in svbF7 bound | 392 | 0 |
| absent svbF7 bound | 8380 | 6355 |
pvalue_fixe = phyper(392 - 1, 295, 15127 - 295, 8772)
pvalue_nonfixe = phyper(324 - 1, 938, 15688 - 938, 8765)
presence = c(392,8380)
absence = c(0,6355)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me1_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me1_fixe)
presence = c(324,8441)
absence = c(614,6309)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me1_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me1_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 2.462952910^{-42}
La pvalue du test de fisher pour les motifs fixé est de 5.299276610^{-95} Celle du test de fisher pour les motifs non fixé est de 1.095848110^{-41}`
total_svbF7_unbound = 324 + 614
total_svbF7_bound = 392 + 0
percent_svbf7_H3K4me1_unbound = round(100 * 324 / total_svbF7_unbound, 2 )
percent_svbf7_unbound_without_H3K4me1 = round(100 * 614 / total_svbF7_unbound, 2 )
percent_svbf7_H3K4me1_bound = round(100 * 392 / total_svbF7_bound, 2 )
percent_svbf7_bound_without_H3K4me1 = round(100 * 0 / total_svbF7_bound, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me1_absent = c(percent_svbf7_bound_without_H3K4me1,percent_svbf7_unbound_without_H3K4me1)
H3K4me1_present = c(percent_svbf7_H3K4me1_bound,percent_svbf7_H3K4me1_unbound)
data_H3K4me1 = data.frame(etat_svb,H3K4me1_absent,H3K4me1_present)
datatable(data_H3K4me1,rownames = F,filter = "none", colnames = c("Regions without H3K4me1","Regions with H3K4me1" ))fig3 = plot_ly(data_H3K4me1, x = ~etat_svb,y = ~H3K4me1_absent, type = "bar",name = "H3K4me1 absent")
fig3 = fig3 %>% add_trace(y = ~H3K4me1_present, name = "H3K4me1 present")
fig3 = fig3 %>% layout(yaxis = list(title = "percent"))
fig3 = fig3 %>% layout(title = "H3K4me1 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig32.1.4 H3K4me3
| in H3K4me3 | absent H3K4me3 | |
|---|---|---|
| in svbF7 unbound | 92 | 846 |
| absent svbF7 unbound | 4715 | 11329 |
| in H3K4me3 | absent H3K4me3 | |
|---|---|---|
| in svbF7 bound | 222 | 73 |
| absent svbF7 bound | 4586 | 11447 |
pvalue_fixe = phyper(222 - 1, 295, 16328 - 295, 4808)
pvalue_nonfixe = phyper(92 - 1, 938, 16982 - 938, 4807)
presence = c(222,4586)
absence = c(73,11447)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me3_fixe)
presence = c(92,4715)
absence = c(846,11329)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me3_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 1.633496410^{-46}
La pvalue du test de fisher pour les motifs fixé est de 2.255675910^{-60} Celle du test de fisher pour les motifs non fixé est de 1.080796610^{-45}`
total_svbF7_unbound_H3K4me3 = 92 + 846
total_svbF7_bound_H3K4me3 = 222 + 73
percent_svbf7_H3K4me3_unbound = round(100 * 92 / total_svbF7_unbound_H3K4me3, 2 )
percent_svbf7_unbound_without_H3K4me3 = round(100 * 846 / total_svbF7_unbound_H3K4me3, 2 )
percent_svbf7_H3K4me3_bound = round(100 * 222 / total_svbF7_bound_H3K4me3, 2 )
percent_svbf7_bound_without_H3K4me3 = round(100 * 73 / total_svbF7_bound_H3K4me3, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me3_absent = c(percent_svbf7_bound_without_H3K4me3,percent_svbf7_unbound_without_H3K4me3)
H3K4me3_present = c(percent_svbf7_H3K4me3_bound,percent_svbf7_H3K4me3_unbound)
data_H3K4me3 = data.frame(etat_svb,H3K4me3_absent,H3K4me3_present)
datatable(data_H3K4me3,rownames = F,filter = "none",colnames = c("Regions without H3K4me3","Regions with H3K4me3" ))fig4 = plot_ly(data_H3K4me3, x = ~etat_svb,y = ~H3K4me3_absent, type = "bar",name = "H3K4me3 absent")
fig4 = fig4 %>% add_trace(y = ~H3K4me3_present, name = "H3K4me3 present")
fig4 = fig4 %>% layout(yaxis = list(title = "percent"))
fig4 = fig4 %>% layout(title = "H3K4me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig42.2 Comparaison avec les histones pour les motifs fixés ou non avec les pics S2 uniquement
2.2.1 H3K27ac
| in H3K27ac | absent H3K27ac | |
|---|---|---|
| in svbF7 unbound | 193 | 745 |
| absent svbF7 unbound | 4955 | 7979 |
| in H3K27ac | absent H3K27ac | |
|---|---|---|
| in svbF7 bound | 169 | 24 |
| absent svbF7 bound | 4981 | 8782 |
pvalue_fixe = phyper(169 - 1, 193, 13956 - 193, 5150)
pvalue_nonfixe = phyper(193 - 1, 938, 13872 - 938, 5148)
presence = c(169,4981)
absence = c(24,8782)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27ac_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27ac_fixe)
presence = c(193,4955)
absence = c(745,7979)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27ac_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27ac_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 3.611226810^{-30}
La pvalue du test de fisher pour les motifs fixé est de 6.843549410^{-49} Celle du test de fisher pour les motifs non fixé est de 1.590738210^{-29}`
total_svbF7_unbound_H3K27ac = 193 + 745
total_svbF7_bound_H3K27ac = 169 + 24
percent_svbf7_H3K27ac_unbound = round(100 * 193 / total_svbF7_unbound_H3K27ac, 2 )
percent_svbf7_unbound_without_H3K27ac = round(100 * 745 / total_svbF7_unbound_H3K27ac, 2 )
percent_svbf7_H3K27ac_bound = round(100 * 169 / total_svbF7_bound_H3K27ac, 2 )
percent_svbf7_bound_without_H3K27ac = round(100 * 24 / total_svbF7_bound_H3K27ac, 2 )
etat_svb = c("svbF7_bound","svb_unbound")
H3K27ac_absent = c(percent_svbf7_bound_without_H3K27ac,percent_svbf7_unbound_without_H3K27ac)
H3K27ac_present = c(percent_svbf7_H3K27ac_bound,percent_svbf7_H3K27ac_unbound)
data_H3K27ac = data.frame(etat_svb,H3K27ac_absent,H3K27ac_present)
datatable(data_H3K27ac,rownames = F,filter = "none",colnames = c("Regions without H3K27ac","Regions with H3K27ac" ))fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb")
fig1fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig12.2.2 H3K27me3
| in H3K27me3 | absent H3K27me3 | |
|---|---|---|
| in svbF7 unbound | 1241 | 0 |
| absent svbF7 unbound | 12191 | 4566 |
| in H3K27me3 | absent H3K27me3 | |
|---|---|---|
| in svbF7 bound | 125 | 68 |
| absent svbF7 bound | 13313 | 4633 |
pvalue_fixe = phyper(125 - 1, 193, 18139 - 193, 13438)
pvalue_nonfixe = phyper(1241 - 1, 938, 17998 - 938, 13432)
presence = c(125,13313)
absence = c(68,4633)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27me3_fixe)
presence = c(1241,12191)
absence = c(0,4566)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27me3_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 0.0015224 Celle du test de hypergéométrique pour les motifs non fixé est de 1
La pvalue du test de fisher pour les motifs fixé est de 0.0037899 Celle du test de fisher pour les motifs non fixé est de 8.667719310^{-165}`
total_svbF7_unbound_H3K27me3 = 1241 + 0
total_svbF7_bound_H3K27me3 = 125 + 68
percent_svbf7_H3K27me3_unbound = round(100 * 1241 / total_svbF7_unbound_H3K27me3, 2 )
percent_svbf7_unbound_without_H3K27me3 = round(100 * 0 / total_svbF7_unbound_H3K27me3, 2 )
percent_svbf7_H3K27me3_bound = round(100 * 125 / total_svbF7_bound_H3K27me3, 2 )
percent_svbf7_bound_without_H3K27me3 = round(100 * 68 / total_svbF7_bound_H3K27me3, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K27me3_absent = c(percent_svbf7_bound_without_H3K27me3,percent_svbf7_unbound_without_H3K27me3)
H3K27me3_present = c(percent_svbf7_H3K27me3_bound,percent_svbf7_H3K27me3_unbound)
data_H3K27me3 = data.frame(etat_svb,H3K27me3_absent,H3K27me3_present)
datatable(data_H3K27me3,rownames = F,filter = "none",colnames = c("Regions without H3K27me3","Regions with H3K27me3" ))fig2 = plot_ly(data_H3K27me3, x = ~etat_svb,y = ~H3K27me3_absent, type = "bar",name = "H3K27me3 absent")
fig2 = fig2 %>% add_trace(y = ~H3K27me3_present, name = "H3K27me3 present")
fig2 = fig2 %>% layout(yaxis = list(title = "percent"))
fig2 = fig2 %>% layout(title = "H3K27me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig22.2.3 H3K4me1
| in H3K4me1 | absent H3K4me1 | |
|---|---|---|
| in svbF7 unbound | 324 | 614 |
| absent svbF7 unbound | 8441 | 6309 |
| in H3K4me1 | absent H3K4me1 | |
|---|---|---|
| in svbF7 bound | 246 | 0 |
| absent svbF7 bound | 8522 | 7027 |
pvalue_fixe = phyper(246 - 1, 193, 15795 - 193, 8768)
pvalue_nonfixe = phyper(324 - 1, 938, 15688 - 938, 8765)
presence = c(246,8522)
absence = c(0,7027)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me1_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me1_fixe)
presence = c(324,8441)
absence = c(614,6309)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me1_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me1_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 2.462952910^{-42}
La pvalue du test de fisher pour les motifs fixé est de 5.06375710^{-64} Celle du test de fisher pour les motifs non fixé est de 1.095848110^{-41}`
total_svbF7_unbound = 324 + 614
total_svbF7_bound = 246 + 0
percent_svbf7_H3K4me1_unbound = round(100 * 324 / total_svbF7_unbound, 2 )
percent_svbf7_unbound_without_H3K4me1 = round(100 * 614 / total_svbF7_unbound, 2 )
percent_svbf7_H3K4me1_bound = round(100 * 246 / total_svbF7_bound, 2 )
percent_svbf7_bound_without_H3K4me1 = round(100 * 0 / total_svbF7_bound, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me1_absent = c(percent_svbf7_bound_without_H3K4me1,percent_svbf7_unbound_without_H3K4me1)
H3K4me1_present = c(percent_svbf7_H3K4me1_bound,percent_svbf7_H3K4me1_unbound)
data_H3K4me1 = data.frame(etat_svb,H3K4me1_absent,H3K4me1_present)
datatable(data_H3K4me1,rownames = F,filter = "none", colnames = c("Regions without H3K4me1","Regions with H3K4me1" ))fig3 = plot_ly(data_H3K4me1, x = ~etat_svb,y = ~H3K4me1_absent, type = "bar",name = "H3K4me1 absent")
fig3 = fig3 %>% add_trace(y = ~H3K4me1_present, name = "H3K4me1 present")
fig3 = fig3 %>% layout(yaxis = list(title = "percent"))
fig3 = fig3 %>% layout(title = "H3K4me1 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig32.2.4 H3K4me3
| in H3K4me3 | absent H3K4me3 | |
|---|---|---|
| in svbF7 unbound | 92 | 846 |
| absent svbF7 unbound | 4715 | 11329 |
| in H3K4me3 | absent H3K4me3 | |
|---|---|---|
| in svbF7 bound | 139 | 54 |
| absent svbF7 bound | 4668 | 12246 |
pvalue_fixe = phyper(139 - 1, 193, 17107 - 193, 4807)
pvalue_nonfixe = phyper(92 - 1, 938, 16982 - 938, 4807)
presence = c(139,4668)
absence = c(54,12246)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me3_fixe)
presence = c(92,4715)
absence = c(846,11329)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me3_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 1.633496410^{-46}
La pvalue du test de fisher pour les motifs fixé est de 5.465460810^{-37} Celle du test de fisher pour les motifs non fixé est de 1.080796610^{-45}`
total_svbF7_unbound_H3K4me3 = 92 + 846
total_svbF7_bound_H3K4me3 = 139 + 54
percent_svbf7_H3K4me3_unbound = round(100 * 92 / total_svbF7_unbound_H3K4me3, 2 )
percent_svbf7_unbound_without_H3K4me3 = round(100 * 846 / total_svbF7_unbound_H3K4me3, 2 )
percent_svbf7_H3K4me3_bound = round(100 * 139 / total_svbF7_bound_H3K4me3, 2 )
percent_svbf7_bound_without_H3K4me3 = round(100 * 54 / total_svbF7_bound_H3K4me3, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me3_absent = c(percent_svbf7_bound_without_H3K4me3,percent_svbf7_unbound_without_H3K4me3)
H3K4me3_present = c(percent_svbf7_H3K4me3_bound,percent_svbf7_H3K4me3_unbound)
data_H3K4me3 = data.frame(etat_svb,H3K4me3_absent,H3K4me3_present)
datatable(data_H3K4me3,rownames = F,filter = "none",colnames = c("Regions without H3K4me3","Regions with H3K4me3" ))fig4 = plot_ly(data_H3K4me3, x = ~etat_svb,y = ~H3K4me3_absent, type = "bar",name = "H3K4me3 absent")
fig4 = fig4 %>% add_trace(y = ~H3K4me3_present, name = "H3K4me3 present")
fig4 = fig4 %>% layout(yaxis = list(title = "percent"))
fig4 = fig4 %>% layout(title = "H3K4me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig42.3 Comparaison avec les histones pour les motifs fixés ou non avec les pics dans les embryons
2.3.1 H3K27ac
| in H3K27ac | absent H3K27ac | |
|---|---|---|
| in svbF7 unbound | 193 | 745 |
| absent svbF7 unbound | 4955 | 7979 |
| in H3K27ac | absent H3K27ac | |
|---|---|---|
| in svbF7 bound | 98 | 401 |
| absent svbF7 bound | 5050 | 8036 |
pvalue_fixe = phyper(98 - 1, 499, 13585 - 499, 5148)
pvalue_nonfixe = phyper(193 - 1, 938, 13872 - 938, 5148)
presence = c(98,5050)
absence = c(401,8036)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27ac_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27ac_fixe)
presence = c(193,4955)
absence = c(745,7979)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27ac_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27ac_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 9.28454310^{-20} Celle du test de hypergéométrique pour les motifs non fixé est de 3.611226810^{-30}
La pvalue du test de fisher pour les motifs fixé est de 3.637514510^{-19} Celle du test de fisher pour les motifs non fixé est de 1.590738210^{-29}`
total_svbF7_unbound_H3K27ac = 193 + 745
total_svbF7_bound_H3K27ac = 98 + 401
percent_svbf7_H3K27ac_unbound = round(100 * 193 / total_svbF7_unbound_H3K27ac, 2 )
percent_svbf7_unbound_without_H3K27ac = round(100 * 745 / total_svbF7_unbound_H3K27ac, 2 )
percent_svbf7_H3K27ac_bound = round(100 * 98 / total_svbF7_bound_H3K27ac, 2 )
percent_svbf7_bound_without_H3K27ac = round(100 * 401 / total_svbF7_bound_H3K27ac, 2 )
etat_svb = c("svbF7_bound","svb_unbound")
H3K27ac_absent = c(percent_svbf7_bound_without_H3K27ac,percent_svbf7_unbound_without_H3K27ac)
H3K27ac_present = c(percent_svbf7_H3K27ac_bound,percent_svbf7_H3K27ac_unbound)
data_H3K27ac = data.frame(etat_svb,H3K27ac_absent,H3K27ac_present)
datatable(data_H3K27ac,rownames = F,filter = "none",colnames = c("Regions without H3K27ac","Regions with H3K27ac" ))fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb")
fig1fig1 = plot_ly(data_H3K27ac, x = ~etat_svb,y = ~H3K27ac_absent, type = "bar",name = "H3K27ac absent")
fig1 = fig1 %>% add_trace(y = ~H3K27ac_present, name = "H3K27ac present")
fig1 = fig1 %>% layout(yaxis = list(title = "percent"))
fig1 = fig1 %>% layout(title = "H3K27ac enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig12.3.2 H3K27me3
| in H3K27me3 | absent H3K27me3 | |
|---|---|---|
| in svbF7 unbound | 1241 | 0 |
| absent svbF7 unbound | 12191 | 4566 |
| in H3K27me3 | absent H3K27ac | |
|---|---|---|
| in svbF7 bound | 672 | 0 |
| absent svbF7 bound | 12763 | 4083 |
pvalue_fixe = phyper(672 - 1, 499, 17518 - 499, 13435)
pvalue_nonfixe = phyper(1241 - 1, 938, 17998 - 938, 13432)
presence = c(672,12763)
absence = c(0,4083)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K27me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K27me3_fixe)
presence = c(1241,12191)
absence = c(0,4566)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K27me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K27me3_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 1 Celle du test de hypergéométrique pour les motifs non fixé est de 1
La pvalue du test de fisher pour les motifs fixé est de 1.19376610^{-79} Celle du test de fisher pour les motifs non fixé est de 8.667719310^{-165}`
total_svbF7_unbound_H3K27me3 = 1241 + 0
total_svbF7_bound_H3K27me3 = 672 + 0
percent_svbf7_H3K27me3_unbound = round(100 * 1241 / total_svbF7_unbound_H3K27me3, 2 )
percent_svbf7_unbound_without_H3K27me3 = round(100 * 0 / total_svbF7_unbound_H3K27me3, 2 )
percent_svbf7_H3K27me3_bound = round(100 * 672 / total_svbF7_bound_H3K27me3, 2 )
percent_svbf7_bound_without_H3K27me3 = round(100 * 0 / total_svbF7_bound_H3K27me3, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K27me3_absent = c(percent_svbf7_bound_without_H3K27me3,percent_svbf7_unbound_without_H3K27me3)
H3K27me3_present = c(percent_svbf7_H3K27me3_bound,percent_svbf7_H3K27me3_unbound)
data_H3K27me3 = data.frame(etat_svb,H3K27me3_absent,H3K27me3_present)
datatable(data_H3K27me3,rownames = F,filter = "none",colnames = c("Regions without H3K27me3","Regions with H3K27me3" ))fig2 = plot_ly(data_H3K27me3, x = ~etat_svb,y = ~H3K27me3_absent, type = "bar",name = "H3K27me3 absent")
fig2 = fig2 %>% add_trace(y = ~H3K27me3_present, name = "H3K27me3 present")
fig2 = fig2 %>% layout(yaxis = list(title = "percent"))
fig2 = fig2 %>% layout(title = "H3K27me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig22.3.3 H3K4me1
| in H3K4me1 | absent H3K4me1 | |
|---|---|---|
| in svbF7 unbound | 324 | 614 |
| absent svbF7 unbound | 8441 | 6309 |
| in H3K4me1 | absent H3K4me1 | |
|---|---|---|
| in svbF7 bound | 259 | 240 |
| absent svbF7 bound | 8507 | 6316 |
pvalue_fixe = phyper(259 - 1, 499, 15322 - 499, 8766)
pvalue_nonfixe = phyper(324 - 1, 938, 15688 - 938, 8765)
presence = c(259,8507)
absence = c(240,6316)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me1_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me1_fixe)
presence = c(324,8441)
absence = c(614,6309)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me1_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me1_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 0.0066816 Celle du test de hypergéométrique pour les motifs non fixé est de 2.462952910^{-42}
La pvalue du test de fisher pour les motifs fixé est de 0.016689 Celle du test de fisher pour les motifs non fixé est de 1.095848110^{-41}`
total_svbF7_unbound = 324 + 614
total_svbF7_bound = 246 + 0
percent_svbf7_H3K4me1_unbound = round(100 * 324 / total_svbF7_unbound, 2 )
percent_svbf7_unbound_without_H3K4me1 = round(100 * 614 / total_svbF7_unbound, 2 )
percent_svbf7_H3K4me1_bound = round(100 * 246 / total_svbF7_bound, 2 )
percent_svbf7_bound_without_H3K4me1 = round(100 * 0 / total_svbF7_bound, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me1_absent = c(percent_svbf7_bound_without_H3K4me1,percent_svbf7_unbound_without_H3K4me1)
H3K4me1_present = c(percent_svbf7_H3K4me1_bound,percent_svbf7_H3K4me1_unbound)
data_H3K4me1 = data.frame(etat_svb,H3K4me1_absent,H3K4me1_present)
datatable(data_H3K4me1,rownames = F,filter = "none", colnames = c("Regions without H3K4me1","Regions with H3K4me1" ))fig3 = plot_ly(data_H3K4me1, x = ~etat_svb,y = ~H3K4me1_absent, type = "bar",name = "H3K4me1 absent")
fig3 = fig3 %>% add_trace(y = ~H3K4me1_present, name = "H3K4me1 present")
fig3 = fig3 %>% layout(yaxis = list(title = "percent"))
fig3 = fig3 %>% layout(title = "H3K4me1 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig32.3.4 H3K4me3
| in H3K4me3 | absent H3K4me3 | |
|---|---|---|
| in svbF7 unbound | 92 | 846 |
| absent svbF7 unbound | 4715 | 11329 |
| in H3K4me3 | absent H3K4me3 | |
|---|---|---|
| in svbF7 bound | 58 | 441 |
| absent svbF7 bound | 4749 | 11305 |
pvalue_fixe = phyper(58 - 1, 499, 16553 - 499, 4807)
pvalue_nonfixe = phyper(92 - 1, 938, 16982 - 938, 4807)
presence = c(58,4749)
absence = c(441,11305)
svbF7 = c("in svbF7 bound", "absent svbF7 bound")
contingence_H3K4me3_fixe = data.frame(presence,absence, row.names = svbF7)
fisher = fisher.test(contingence_H3K4me3_fixe)
presence = c(92,4717)
absence = c(849,11329)
svbF7 = c("in svbF7 unbound", "absent svbF7 unbound")
contingence_H3K4me3_nonfixe = data.frame(presence,absence, row.names = svbF7)
fisher_nonfixe = fisher.test(contingence_H3K4me3_nonfixe)La pvalue du test de hypergéométrique pour les motifs fixé est de 8.590137410^{-22} Celle du test de hypergéométrique pour les motifs non fixé est de 1.633496410^{-46}
La pvalue du test de fisher pour les motifs fixé est de 4.7061110^{-21} Celle du test de fisher pour les motifs non fixé est de 4.936237910^{-46}`
total_svbF7_unbound_H3K4me3 = 92 + 846
total_svbF7_bound_H3K4me3 = 58 + 441
percent_svbf7_H3K4me3_unbound = round(100 * 92 / total_svbF7_unbound_H3K4me3, 2 )
percent_svbf7_unbound_without_H3K4me3 = round(100 * 846 / total_svbF7_unbound_H3K4me3, 2 )
percent_svbf7_H3K4me3_bound = round(100 * 58 / total_svbF7_bound_H3K4me3, 2 )
percent_svbf7_bound_without_H3K4me3 = round(100 * 441 / total_svbF7_bound_H3K4me3, 2 )
etat_svb = c("svbF7_bound","svbF7_unbound")
H3K4me3_absent = c(percent_svbf7_bound_without_H3K4me3,percent_svbf7_unbound_without_H3K4me3)
H3K4me3_present = c(percent_svbf7_H3K4me3_bound,percent_svbf7_H3K4me3_unbound)
data_H3K4me3 = data.frame(etat_svb,H3K4me3_absent,H3K4me3_present)
datatable(data_H3K4me3,rownames = F,filter = "none",colnames = c("Regions without H3K4me3","Regions with H3K4me3" ))fig4 = plot_ly(data_H3K4me3, x = ~etat_svb,y = ~H3K4me3_absent, type = "bar",name = "H3K4me3 absent")
fig4 = fig4 %>% add_trace(y = ~H3K4me3_present, name = "H3K4me3 present")
fig4 = fig4 %>% layout(yaxis = list(title = "percent"))
fig4 = fig4 %>% layout(title = "H3K4me3 enrichment on svbF7 bound or not by Svb", barmode = "stack")
fig43 Conclusion
Nous observons que les motifs svbF7 communs fixés entre les S2 et les embryons montrent un enrichissement en H3K4me1, H3K4me3 et H3K27ac. Cet enrichissement est également visible pour les motifs svbF7 fixé uniquement dans les embryons. Les motifs svbf7 des embryons sont enrichi en H3K27me3 et H3K4me1.